Issue #257

Oct 25 2018

Editor Picks

A neural network designs Halloween costumesIt’s hard to come up with ideas for Halloween costumes, especially when it seems like all the good ones are taken. And don’t you hate showing up at a party only to discover that there’s *another* pajama cardinalfish? So, I wanted to find out if a neural network could help invent Halloween costumes...

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Trellis Networks for Sequence ModelingWe present trellis networks, a new architecture for sequence modeling. On the one hand, a trellis network is a temporal convolutional network with special structure, characterized by weight tying across depth and direct injection of the input into deep layers. On the other hand, we show that truncated recurrent networks are equivalent to trellis networks with special sparsity structure in their weight matrices. ...

deeplabv3PyTorch implementation of DeepLabV3, trained on the Cityscapes dataset...

Partial Convolutions for Image Inpainting using KerasKeras implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions"... it's been a great learning experience for me to implement the architecture, the partial convolutional layer, and the loss functions...

Curiosity and Procrastination in Reinforcement LearningReinforcement learning (RL) is one of the most actively pursued research techniques of machine learning, in which an artificial agent receives a positive reward when it does something right, and negative reward otherwise. This carrot-and-stick approach is simple and universal, and allowed DeepMind to teach the DQN algorithm to play vintage Atari games and AlphaGoZero to play the ancient game of Go. This is also how OpenAI taught its OpenAI-Five algorithm to play the modern video game Dota, and how Google taught robotic arms to grasp new objects. However, despite the successes of RL, there are many challenges to making it an effective technique...

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Trellis Networks for Sequence ModelingWe present trellis networks, a new architecture for sequence modeling. On the one hand, a trellis network is a temporal convolutional network with special structure, characterized by weight tying across depth and direct injection of the input into deep layers. On the other hand, we show that truncated recurrent networks are equivalent to trellis networks with special sparsity structure in their weight matrices. ...